Characteristics

Bands are:

sta <- read_stars("charac_five_attr/all_2017-01-08_2018-12-29.tif")
study_area <- st_transform(study_area, crs=st_crs(sta))
sta_small <- sta[study_area[1,]]
plot(sta_small[,,,1], main = "Change Count")
plot(sta_small[,,,2], main = "Change Frequency")
plot(sta_small[,,,3], main = "Change Range")
plot(sta_small[,,,4], main = "Mean")
plot(sta_small[,,,5], main = "Threshold Count")

Use Case Example: Count and Range

# conversion to raster scales to 0:255
sta_small_count <- as(sta_small[,,,1], "Raster")
sta_small_range <- as(sta_small[,,,3], "Raster")
# NDI
ras <- (sta_small_count - sta_small_range) / (sta_small_count + sta_small_range)
# color
colo = viridisLite::inferno(20)
plot(ras, col = colo)

Full Extent RGB: R = Count, G = Frequency, B = Range

red -> much change, green -> much stability over time, blue -> high change amplitues

ras <- raster::stack("charac_five_attr/all_2017-01-08_2018-12-29.tif")
plotRGB(ras, r=1, g=2, b=3, stretch = "lin")

Full Extent RGB: R = Count, G = Frequency, B = Threshold Count

red -> much change, green -> much stability over time, blue -> high water threshold counts

ras <- raster::stack("charac_five_attr/all_2017-01-08_2018-12-29.tif")
ras <- crop(ras, study_area[1,])
ras <- mask(ras, study_area[1,])
plotRGB(ras, r=1, g=2, b=5, stretch = "lin")

Further Possibillities